The medical record for a neuro-oncology patient is complex, consisting of typically a large number of both text and imaging data. It includes descriptions of prior observations, interpretations, and interventions which need to be integrated into decisions regarding current patient care. An appropriate review of a patient's medical record often requires that a physician review multiple clinical documents while mentally noting issues related to what the findings were, the chronology of events, spatial/temporal patterns of disease progression, the effects of interventions, and the possible causal lines of explanation of observed findings. Additionally, imaging data and imaging- derived conclusions are poorly integrated into patient care and management decisions. The physician also needs to filter out those pieces of information not related to the current clinical context of care. Given the time constraints, data complexity and data volume associated with chronic patient cases, an appropriate review of a patient's chart is in reality rarely performed. Additionally, the lack of tools for formalizing the representation of the accounts of current and prior cases impedes the development of clinical databases that can be ultimately used to learn patterns of disease. This proposal addresses the development of a system for facilitating the review of clinical patient data intended to promote an orderly process of medical problem understanding and care. The specific aims of the proposal are summarized as follows: 1) Development of a backend tool to facilitate the structured representation of observations, events, and inferences stated within medical reports. 2) Development of an application interface for visualizing, navigating, and editing structured patient data. 3) Evaluation of the effectiveness of the application in the domain of neuro-oncology. Relation to public health. If the goals of this proposal can be realized, neuro-oncologist should be able to more easily seek desired patient data and detect patterns of evidence as compared to the current mode of operation (HIS, RIS, PACS). The structuring tools should lead to improvements in the quality of clinical research databases.